Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/66268
Authors: 
Severance-Lossin, E.
Sperlich, Stefan
Year of Publication: 
1997
Series/Report no.: 
Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1997,30
Abstract: 
Additive regression models have a long history in nonparametric regression. It is well known that these models can be estimated at the one dimensional rate. Until recently, however, these models have been estimated by a backfitting procedure. Although the procedure converges quickly, its iterative nature makes analyzing its statistical properties difficult. Furthermore it is unclear how to estimate derivatives with this approach since it does not give a closed form for the estimator. Recently, an integration approach has been studied that allows for the derivation of a closed form for the estimator. This paper extends this approach to the simultaneous estimation of both the function and its derivatives by combining the integration procedure with a local polynomial approach. Finally the merits of this procedure with respect to the estimation of a production function subject to separability conditions are discussed. The procedure is applied to livestock production data from Wisconsin. It is shown that there is some evidence of increasing return to scale for larger farms.
Subjects: 
Nonparametric Regression
Additive Models
Derivative Estimation
Production Function
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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